When it comes to data science in the enterprise, organizations often face a culture of self-interest that leads to unnecessary friction between the Data Science and Software engineering teams, causing inefficiencies, and ultimately a failure to realize the full potential of data science. In this talk, we’ll show how Jupyter Notebooks combined with the PixieDust open source library can address the expectations and challenges around data science, including the shortage of technical expertise, overly complex and inaccessible analytics tools and more.

A crash course on deploying Python applications to Heroku. We'll take a pre-made Django app, spin it up locally, then deploy it to Heroku. We'll then go over the tools that Heroku provides for managing your applications.

Continuing with tradition, our sponsor workshop session features three awesome half-hour Python tech talks as they relate to Google. Hear about Python tools we’ve built in-house, using Python with Google developer tools to build your web & mobile applications with or best practices on how we use Python internally at Google. You’re invited to stop by and hear from a cadre of world-class Google engineers from around the world! :-)

In this workshop, we'll guide you through the process and tools needed to build your first Slack bot. We'll go over our Python SDKs, walk through an example app and talk about what's going on under-the-hood as your app interacts with Slack's APIs.
This workshop will be beginner-friendly, but also allow those with prior experience with Slack to learn about new features, tools and ask us questions directly.

In this workshop we’ll explore working with complex dependency trees in Python, learn about how to quickly configure virtual environments, as well as how you can implement zero-discipline runtime security scanning for your applications.
ActiveState’s ActivePython distribution and the newly launched ActiveState platform provide solutions to these problems in simple and powerful ways. During this workshop, we’ll walk through:
- How you can use the ActivePython distribution to have a pre-configured, pre-built environment for many common development tasks and avoid dealing with complex build steps for dependencies.
- How to configure a virtual environment for your project
- How to integrate ActiveState’s runtime interpreter plugin to either ActivePython or your existing Python distribution to achieve zero-discipline security reporting
- A demonstration of how the new ActiveState platform sets you up to solve these problems and more in a simple, powerful manner"

Developers have many choices when it comes to writing Python code from editors to IDEs, from free tools to paid, from tools designed specifically for their platform to tools running on many, from open source to closed source tools and so on… In this demo-driven session, we’ll show you why we think the cross-platform, free, and open source Visual Studio Code will become your favorite tool for all your Python needs. From editing to linting, to debugging and more, you will learn how to get started, as well as tips and tricks to save you time in your everyday development lifecycle. You will also learn when to consider Visual Studio 2017, which for certain scenarios (such as mixed C and Python development), can offer you more than any other Python tool on the planet.

In dealing with hundreds of Data Science teams around the world, our team has had a consistent request: A proven, standardized methodology for Data Science that folds into standard IT practices (such as SDLC’s and DevOps) and governance. The Team Data Science Process (TDSP) is a robust, yet flexible, fully-documented and defined process you can use for consistent, successful Data Science projects. The TDSP takes into account all phases, roles, and skills in a solution. Buck Woody, an Applied Data Scientist from Microsoft Research and AI, will explain how the TDSP works, provide you resources to use in your organization, and walk you through a practical example using Python.

Audience level: Intermediate
We'll look at the wide variety of ways that we can leverage Python functions. This will show provide helpful background in ordinary functions, as well as callable objects and lambdas. We'll look closely at how to use generator functions, also. The fifth type of function is a function wraps a special method, like len().